Ecological Assessments of Activities of Daily Living and Personal Experiences with Mobus, An Assistive Technology for Cognition: A Pilot Study in Schizophrenia
Bibliographic record
Abstract
Mobus is a cognitive orthotic designed for people with difficulties managing Activities of Daily Living (ADL), as encountered in schizophrenia. It provides a schedule manager as well as the possibility to report occurrences of symptomatic experiences. Receiving this information by Internet, caregivers can assist the patient rehabilitation process. Our aim was to explore the use and satisfaction of Mobus by people with schizophrenia. Nine outpatients tested Mobus for 6 weeks. Indicators of cognitive functioning and autonomy were measured with the CAmbridge Neuropsychological Tests Automated Battery (CANTAB) and the Independant Living Skills Scale (ILSS). On average, 42.6% of the planned ADL were validated and more than 1 symptom per week were reported. Mainly because of technical breakdown, more than 50% of the outpatients evaluated the Mobus satisfaction below 1.7/5, nevertheless 3 participants appreciated it greatly. Some enhancements were found on subscales of CANTAB and ILSS and some participants reported that they acquired planning skills by using Mobus. To ensure ease of use, refinements are needed from rehabilitation and technical approaches, especially to personalize the device. Discussions on ethical and methodological issues lead to an improved version of Mobus that will be tested with a larger sample size.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".